System for validation and interpreting results of antimicrobial susceptibility tests of micro-organisms

ABSTRACT

The invention concerns a method for analysing results of antimicrobial susceptibility tests of micro-organisms, the test consisting in summarily identifying which species the micro-organism belongs to and measuring the minimum inhibitory concentrations (CMI) of several antimicrobial agents for said micro-organism. The method uses a database classifying the micro-organism species and the resistance mechanism to various antimicrobial agents, and containing, for each species and each resistance mechanism, parameters characteristic of the frequency distribution of minimum inhibitory concentrations for a group of antimicrobial agents.

[0001] The present invention relates to a method for analyzing testresults of bacteria susceptibility to antibiotics in order to assistdoctors in prescribing a treatment. The analysis can more generallyextend to tests of antimicrobial agents on micro-organisms.

[0002] A conventional analysis method consists in performingidentification and antibiogram tests on a bacterial strain present in asample, for example the blood of a patient. The identification aims atknowing more or less precisely the bacterial species to which thestudied strain belongs. It is in particular performed by a macroscopicand microscopic observation, and carrying out tests by means of specificbiochemical reagents. In general, the sole knowledge of the bacterialspecies is not sufficient to predict the efficiency of a givenantibiotic on the studied strain. Indeed, for each family ofantibiotics, the strains of a same species can have different resistancemechanisms, which will not always deactivate the same antibiotics withinthe family. The antibiogram consists in bringing together the studiedbacterial strain and different antibiotics likely to be efficient onthis strain. It is based on a more or less accurate measurement of theMinimum Inhibitory Concentration (MIC) of each of the antibiotics forthe studied strain, that is, the minimum antibiotic concentration forwhich the strain ceases development.

[0003] Expert committees establish a first MIC threshold under which thetested species is designated “susceptible”, and a second threshold abovewhich the species is designated “resistant”. Between the two thresholds,the species is designated “intermediate”. This is the informationgenerally provided to doctors.

[0004] Before being used by doctors as a basis to prescribe anantibiotic treatment, the result of the antibiogram is ofteninterpreted. The aim of this interpretation is to detect possible testerrors, or risks of inconsistency between the behavior of the studiedstrain confronted to a given antibiotic in vitro during the test and invivo in the patient's organism during the treatment. This approach ismost often based on semi-empirical rules. For example, it enablesdetecting as erroneous a result “susceptible to an antibiotic” when thestudied strain belongs to a species systematically resistant to thisantibiotic, or resistant to a related antibiotic known as systematicallymore active. In some cases, it is based on the knowledge of the possibleresistance mechanisms for the species to which the studied strainbelongs.

[0005] It is thus possible to correct or comment the results given forsome antibiotics, when some elements hint that the strain has aresistance mechanism which may express less in vitro than in theorganism. This interpretation also involves notions in appreciating therisk for the patient: in case of doubt for an antibiotic, it isgenerally preferred to state that a strain is resistant, if there areother antibiotics available for a treatment, to which the strain hasbeen found to be susceptible with unambiguously.

[0006] Present analysis systems perform the test in an automated way andare able to indicate, for each tested antibiotic, whether the species isresistant, intermediate or susceptible. Further, some of these systemsenable an automation of part of the interpretation, especially by usinga rule database. The rule databases implemented in these systems mostoften reproduce the semi-empirical rules conventionally used. Now, theserules are efficient only to detect and correct some predetermined errorcases. A problem thus is the implementation of an interpretation methodenabling detection of all error types and the provision, if possible, oftheir correction.

[0007] The recognition of the resistance mechanisms which may poorlyexpress in vitro is required to correct or comment the results. The ruledatabases implemented in present systems are based on the classificationas “susceptible”, “intermediate”, or “resistant”, and closely depend onthe list of tested antibiotics. In a great number of cases, they do notenable accurate detection of the resistance mechanism.

[0008] Further, the pairs of MIC thresholds determining the“susceptible”, “intermediate”, and “resistant” categories, being fixedby national expert committees, are likely to be modified in time anddiffer from one country to another, or even sometimes from onelaboratory to another in some countries. The same occurs forrecommendations concerning the required behavior in case a resistancemechanism that may poorly express in vitro shows up. Thus, differentrule bases corresponding to the interpretative choices of the differentnational expert committees and enabling adaptation of the rulesaccording to the laboratories have to be provided. Such rule bases areparticularly complex and their development amounts to considerable work.

[0009] An object of the present invention is to provide an analysismethod for susceptibility tests which is independent of theinterpretative choices of expert committees, which enables detecting andcorrecting errors without having to forsee the error cases to process,and which provides, in most cases, an accurate indication of theresistance mechanisms of a tested strain for the different antibioticfamilies.

[0010] These objects are achieved by means of a method for analyzingtest results of micro-organism susceptibility to antimicrobial agents,the test consisting of roughly identifying the species to which amicro-organism belongs and of measuring the minimum inhibitoryconcentrations (MIC) of several antimicrobial agents for thismicro-organism. The method uses a database indexing the micro-organismspecies as well as their resistance mechanisms against differentantimicrobial agents, and containing, for each species and eachresistance mechanism, parameters characteristic of statistic MICdistributions for a group of antimicrobial agents.

[0011] According to an embodiment of the invention, the method includesthe steps of extracting from the database the parameters of thedistributions associated with the resistance mechanisms of theidentified species and with the antimicrobial agents used to perform thetest; confronting the MICs measured during the test with the extractedparameters; and indicating that the test is valid when the measured MICscorrespond to the extracted parameters associated with at least onepredetermined resistance mechanism of the identified species.

[0012] According to an embodiment of the invention, the method includesthe step of indicating the predetermined resistance mechanism.

[0013] According to an embodiment of the invention, the method includes,when the test is not valid, a step of determining corrections to beperformed on at least one of the measured MICs, the choice of thecorrections fulfilling predetermined optimality criteria.

[0014] According to an embodiment of the invention, the method includes,when the test is not valid, the steps of extracting from the databasethe parameters of the MIC distributions associated with the resistancemechanisms of other species and with the antimicrobial agents used forthe testing; confronting the measured MICs with the extractedparameters; and determining the species for which at least oneresistance mechanism, per tested antimicrobial agent family, isidentifiable based on the measured MICs.

[0015] According to an embodiment of the invention, the databasecontains information indicating, for species with a given resistancemechanism and for given antimicrobial agents, an in vivo resistancewhich may be higher than the in vitro resistance.

[0016] According to an embodiment of the invention, the distributionparameters stored in the database include the classes of MIC values andthe normalized absolute frequencies, the method including, for anuntested antimicrobial agent, the steps of extracting from the databasethe classes and absolute frequencies associated with the predeterminedresistance mechanism and the untested antimicrobial agent; keeping theclasses for which the absolute frequencies exceed a predeterminedthreshold; confronting the kept classes with two normalized MICthresholds defining “susceptible”, “intermediate”, and “resistant”categories of a micro-organism; and indicating the categories located oneither side of each of the normalized thresholds located in the retainedclasses.

[0017] The foregoing and other objects, features and advantages of thepresent invention will be discussed in detail in the followingnon-limiting description of specific embodiments in connection with theaccompanying drawings.

[0018]FIG. 1 illustrates an example of the contents of a database usedby the method according to the present invention;

[0019]FIG. 2 illustrates a first analysis example according to thepresent invention, unambiguously indicating the resistance mechanism ofa tested species;

[0020]FIG. 3 illustrates an erroneous test case and a measurementcorrection proposal provided by the method according to the presentinvention;

[0021]FIG. 4 illustrates an erroneous test case and a correctionproposal for the species identification;

[0022]FIG. 5 illustrates a susceptibility statement correction based oninformation concerning a greater in vivo resistance of the testedspecies; and

[0023]FIG. 6 illustrates a statement provided by the method according tothe present invention concerning an untested antibiotic.

[0024] The method according to the present invention uses a databaseindexing micro-organism species with their resistance mechanisms todifferent families of antimicrobial agents, and antimicrobial agents.For each antimicrobial agent and each resistance mechanism, the databasestores parameters characteristic of a statistic distribution of minimuminhibitory concentrations (MIC). These parameters may, for example, bean average and a standard deviation, or the lower and upper limits ofthe distribution and an information on its shape, or the normalizedabsolute frequencies of each class of values. Each statisticdistribution is the result of tests performed on a great number ofsamples of individuals of same species and of same resistance mechanism,that is, on a population representative of the species or of theresistance mechanism.

[0025] The resistance mechanisms are characterized by their inactivationspectrum on antibiotics of a same family and do not inactivateantibiotics of the other families. A family is formed of antibioticshaving related biochemical structures and action modes. Accordingly, thedatabase only stores, for a given species and a given resistancemechanism, the statistic MIC distributions associated with antibioticsof a single family.

[0026] The method according to the present invention is meant to becarried out by a computer analysis system, coupled or not to anautomated antibiogram system. A software for carrying out the methodaccording to the present invention and the database may advantageouslyreplace the existing software and rule bases of existing analysissystems.

[0027] The drawings show histograms symbolizing normalized absolutefrequency distributions of the different classes of MIC values (MICdistributions). The normalized absolute frequency of a class is, forexample, the ratio of the absolute frequency of the class to theabsolute frequency of the most populated class. The classes of MICvalues are shown without scale and increase from left to right. Eachhistogram bar illustrates the number of individuals (microbial strains)inhibited by the corresponding antibiotic concentration, this numberbeing counted down from the population not inhibited by the immediatelylower concentration. At the lower limit of a MIC distribution, the mostsusceptible individuals start being affected by the correspondingantibiotic. At the upper limit of the distribution, the last, mostresistant individuals are affected.

[0028]FIG. 1 illustrates an excerpt example of the data base. Forspecies Escherichia coli and the beta-lactam antibiotic family,resistance mechanisms “wild”, “penicillinase”, and “ESBL” (extendedspectrum beta-lactamase) are indexed. Among the antibiotics of thebeta-lactam family, Ampicillin, Cephalotin, and Cefotaxim have beenillustrated.

[0029] The strains having the wild mechanism appear to be susceptible tothe three antibiotics, those having the penicillinase mechanism appearto be resistant to Ampicillin and susceptible to the two otherantibiotics, and finally those with the ESBL mechanism appear to beresistant to the three antibiotics.

[0030]FIG. 2 illustrates a main step of the method according to thepresent invention. By a conventional bacteriological test, a more orless accurate identification of the species to which the studied strainbelongs is performed, for example, by means of biochemicalidentification reagents. This identification provides, for example,species Escherichia coli. At the same time, an antibiogram test isperformed with a number of antibiotics. This antibiogram test provides ameasurement of the MIC of the studied strain for different antibiotics,or enables locating this MIC in a given interval. In this example,Ampicillin, Cephalotin, and Cefotaxim are used.

[0031] Once the tests have been performed, a first step of the methodconsists in extracting from the database the MIC distributionsassociated with the resistance mechanisms of the identified species andwith the tested antibiotics. The measured MICs, provided by theantibiograms and represented by vertical bars in the drawings, are thencompared with the extracted MIC distributions. This comparison can beperformed, for example, by making the normalized absolute frequency ofthe corresponding class of values in the distribution correspond to eachmeasured MIC value. This normalized absolute frequency reflects theadequation of the measured MIC to the distribution extracted from thedatabase.

[0032] The corresponding normalized absolute frequencies are thenaggregated by resistance mechanism (for example, by calculating theaverage or the product of the normalized absolute frequencies), for allthe tested antibiotics in a same family. This aggregation provides asynthetic indicator reflecting the adequation of the MIC measured forthese antibiotics to each resistance mechanism.

[0033] If this synthetic indicator has a sufficiently high value for oneof the resistance mechanisms, this resistance mechanism is the one toidentify and the test is valid.

[0034] The simplified example of FIG. 2 shows that the resistancemechanism to identify is the “wild” mechanism, due to the fact that itis the only mechanism for which each measured MIC corresponds to adistribution associated to the wild mechanism.

[0035] In the situation where several resistance mechanisms have asufficiently high indicator, only that or those having the highestindicators will preferably be kept.

[0036]FIG. 3 illustrates a situation, in the context of the example ofFIG. 2, where the measured MICs do not identify any resistancemechanism. Indeed, for each resistance mechanism, at least one of themeasured MICs is outside the corresponding MIC distribution.

[0037] In this case, the test is indicated as invalid. The method maythen provide a correction for one or several of the measured MICs, bysearching an optimal correction according to a number of criteria. It isin particular desired to minimize the number of corrected antibiotics,to minimize the number of downward corrections, to minimize theamplitude of the corrections, to maximize the adequation level of theuncorrected MICs to the used resistance mechanisms, to maximize thefrequency at which these resistance mechanisms may be encountered. Thisoptimizing may be performed by weighting the different criteria, or bysubmitting them to a hierarchy.

[0038] In the example of FIG. 3, the “wild” mechanism is excluded sincetwo measured MICs out of three would have to be corrected. A resistancemechanism for which it is sufficient to correct a single measured MIC issought in this example, so that all measured MICs correspond to the MICdistributions associated with this resistance mechanism.

[0039] If the resistance mechanism were “penicillinase”, the measuredMIC for Cephalotin should be shifted to the left by a value C1, i.e.decreased, to reach the upper limit of the missing MIC distribution.

[0040] If the resistance mechanism were “ESBL”, the MIC measured forCefotaxim should be shifted to the right by a value C2, i.e. increased,to reach the lower limit of the missing MIC distribution.

[0041] This latter correction C2 will be preferred, essentially forsecurity reasons. Indeed, correction C2 is performed upwards, i.e. thespecies is stated more resistant to Cefotaxim than it seems to be withthe measured MIC values. An upward correction will always be preferredto a downward correction. Of course, among several possible corrections,that of smaller amplitude will be preferred.

[0042] If more than three antibiotics are tested, corrections may beprovided for more than one measured value, the number of correctedvalues having to remain limited.

[0043] The method also provides a correction of the identified species.Indeed, the species identification process always includes some errorrisk. The level of this risk depends in part on the identificationmethod used, and in part on the involved species, some species having,with most usable methods, a non negligible risk of being mistaken withclosely related species.

[0044]FIG. 4 illustrates such a proposal for correcting the speciesidentification. The species was initially identified as “Proteusvulgaris”, and the tested antibiotics are Ampicillin, Augmentin(Amoxicillin-Clavulanic acid), Cephalotin and Ticarcillin.

[0045] For this species, no resistance mechanism corresponds to themeasured MICs. However, the database indexes a species, Proteusmirabilis, the wild resistance mechanism of which perfectly correspondsto the measured MICs. In this case, the system may suggest the Proteusmirabilis species having the “wild” resistance mechanism.

[0046] In most cases, other antibiotic families are tested (the drawingsillustrate a single family). In these cases, before suggesting such aspecies correction, the system tries to identify additional resistancemechanisms for the other tested antibiotic families. A species issuggested only if one resistance mechanism per different antibioticfamily can be identified. Preferably, the system will indicate theidentified resistance mechanism(s) for the species suggested as acorrection.

[0047] In the example of FIG. 4, it should be noted that the speciessuggested as a correction is of the same kind as the initiallyidentified species. Generally, the system will suggest as a correction aspecies having a risk of confusion with the initially identifiedspecies.

[0048] To provide this type of correction, the database may contain, inparticular, groups of species which may be mistaken. When no resistancemechanism is recognized for the initially identified species, the systemsearches a species preferentially in the corresponding group.

[0049]FIG. 5 illustrates the use of inconsistency information betweenthe in vitro and in vivo susceptibilities, that can also be stored inthe database.

[0050] In the example of FIG. 5, species Escherichia coli is testedagain with Ampicillin, Cephalotin and Cefotaxim.

[0051] The measured MICs enable identifying the “ESBL” resistancemechanism. The MIC measured for Cefotaxim indicates that the species israther susceptible. Now, research has shown that the strains having an“ESBL” resistance mechanism can be more resistant to Cefotaxim in vivothan in vitro. Some expert committees thus advocate that the species bestated resistant to Cefotaxim, even though measurements show it to besusceptible in vitro. Such advocating can further take into account theinitially defined susceptibility category by comparing the MICs to thethresholds established by expert committees to define the “susceptible”and “resistant” categories. Thus, for some antibiotics and someresistance mechanisms, it may be advocated to turn into intermediate acategory initially computed as susceptible, and to maintain categoriesinitially computed as resistant.

[0052] Thus, for each antibiotic and each resistance mechanism of aspecies, the database may contain such an in vivo resistanceinformation, which will be taken into account as soon as the testedantibiotic and the identified resistance mechanism correspond. Thesystem also contains the rules for combining this information with thesusceptibility categories defined on the basis of the thresholds.

[0053]FIG. 6 illustrates the use of the information of database toprovide additional indications. As in the preceding example, a strainidentified as species Escherichia coli is tested with Ampicillin,Cephalotin and Cefotaxim. The method reveals the ESBL resistancemechanism.

[0054] Information may be desired on other currently used antibiotics totreat infections by Escherichia coli, such as Ceftriaxon.

[0055] The range in which the MIC of the studied strain for thisantibiotic is probably located is deduced from the MIC distribution ofCeftriaxon for the strains of species Escherichia coli having an ESBLresistance mechanism, by only keeping the classes of MIC values forwhich the normalized absolute frequency exceeds a predeterminedthreshold. As a first intention, the susceptibility category of thestudied strain can be determined by confronting the kept classes withthe two thresholds established by expert committees to define the“susceptible”, “intermediate”, and “resistant” categories. Thus, thesystem will indicate the categories located on either side of eachthreshold included in the kept classes.

[0056] In the example of FIG. 6, all the distribution classes associatedwith the ESBL mechanism and with Ceftriaxon are kept. The two MICthresholds are indicated by bold lines and are both included in the keptclasses. The system then indicates all three “susceptible”,“intermediate”, and “resistant” categories.

[0057] Further, as for Cefotaxim, research has revealed that Escherichiacoll with an ESBL mechanism may be resistant to Ceftriaxon in vitro.Thus, some experts advocate to state that this bacteria is resistant toCeftriaxon, whatever the result of the in vitro MIC determination. Thesystem may thus indicate that the bacterium is resistant to Ceftriaxon,even though Ceftriaxon has not been tested.

[0058] Generally, the system may provide an indication of the probableresistance level of the strain to the untested antibiotics, based on theMIC distribution for this antibiotic and the recognized resistancemechanism, and on the corresponding in vivo resistance information.

[0059] Of course, the present invention is likely to have variousalterations, modifications and improvements which will readily occur tothose skilled in the art. Such alterations, modifications, andimprovements are intended to be part of this disclosure, and areintended to be within the spirit and the scope of the present invention.Accordingly, the foregoing description is by way of example only and isnot intended to be limiting. The present invention is limited only asdefined in the following claims and the equivalents thereto.

What is claimed is:
 1. A method for analyzing test results of microorganism susceptibility to antimicrobial agents, the test consisting of roughly identifying the species to which a micro-organism belongs and of measuring the minimum inhibitory concentrations (MIC) of several antimicrobial agents for this micro-organism, using a database indexing the micro-organism species as well as their resistance mechanisms against different antimicrobial agents, and containing, for each species and each resistance mechanism, parameters characteristic of statistic MIC distributions for a group-of antimicrobial agents.
 2. The method of claim 1 , including the steps of: extracting from the database the parameters of the distributions associated with the resistance mechanisms of the identified species and with the antimicrobial agents used to perform the test; confronting the MICs measured during the test with the extracted parameters; and indicating that the test is valid when the measured MICs correspond to the extracted parameters associated with at least one predetermined resistance mechanism of the identified species.
 3. The method of claim 2 , including the step of indicating the predetermined resistance mechanism.
 4. The method of claim 2 , including, when the test is not valid, a step of determining corrections to be performed on at least one of the measured MICs, the choice of the corrections fulfilling predetermined optimality criteria.
 5. The method of claim 2 , including, when the test is not valid, the steps of: extracting from the database the parameters of the MIC distributions associated with the resistance mechanisms of other species and with the antimicrobial agents used for the testing; confronting the measured MICs with the extracted parameters; and determining the species for which at least one resistance mechanism, per tested antimicrobial agent family, is identifiable based on the measured MICs.
 6. The method of claim 2 , wherein the database contains information indicating, for species with a given resistance mechanism and for given antimicrobial agents, an in vivo resistance which may be higher than the in vitro resistance.
 7. The method of claim 2 , wherein the distribution parameters stored in the database include the classes of MIC values and the normalized absolute frequencies, the method including, for an untested antimicrobial agent, the steps of: extracting from the database the classes and absolute frequencies associated with the predetermined resistance mechanism and the untested antimicrobial agent; keeping the classes for which the absolute frequencies exceed a predetermined threshold; confronting the kept classes with two normalized MIC thresholds defining “susceptible”, “intermediate”, and “resistant” categories of a micro-organism; and indicating the categories located on either side of each of the normalized thresholds located in the retained classes. 